US7907512B1  OFDM and SCOFDM QLM  Google Patents
OFDM and SCOFDM QLM Download PDFInfo
 Publication number
 US7907512B1 US7907512B1 US12/587,687 US58768709A US7907512B1 US 7907512 B1 US7907512 B1 US 7907512B1 US 58768709 A US58768709 A US 58768709A US 7907512 B1 US7907512 B1 US 7907512B1
 Authority
 US
 United States
 Prior art keywords
 data
 qlm
 communications
 ofdm
 subband
 Prior art date
 Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
 Active
Links
 239000010410 layers Substances 0.000 claims abstract description 97
 238000007476 Maximum Likelihood Methods 0.000 claims abstract description 43
 230000000051 modifying Effects 0.000 claims abstract description 40
 230000002596 correlated Effects 0.000 claims description 24
 239000011159 matrix materials Substances 0.000 claims description 14
 230000001702 transmitter Effects 0.000 claims description 14
 230000000875 corresponding Effects 0.000 claims description 12
 239000000562 conjugates Substances 0.000 claims description 9
 239000000969 carrier Substances 0.000 claims description 6
 230000001360 synchronised Effects 0.000 claims description 4
 239000002356 single layers Substances 0.000 claims description 3
 230000003595 spectral Effects 0.000 claims description 3
 238000005192 partition Methods 0.000 claims description 2
 238000005516 engineering processes Methods 0.000 description 5
 238000000926 separation method Methods 0.000 description 4
 238000010276 construction Methods 0.000 description 2
 238000009795 derivation Methods 0.000 description 2
 238000000034 methods Methods 0.000 description 2
 238000004364 calculation methods Methods 0.000 description 1
 238000005070 sampling Methods 0.000 description 1
Images
Classifications

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L5/00—Arrangements affording multiple use of the transmission path
 H04L5/0001—Arrangements for dividing the transmission path
 H04L5/0014—Threedimensional division

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04J—MULTIPLEX COMMUNICATION
 H04J13/00—Code division multiplex systems
 H04J13/0007—Code type
 H04J13/004—Orthogonal
 H04J13/0048—Walsh

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04J—MULTIPLEX COMMUNICATION
 H04J13/00—Code division multiplex systems
 H04J13/10—Code generation
 H04J13/12—Generation of orthogonal codes

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L1/00—Arrangements for detecting or preventing errors in the information received
 H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
 H04L1/0045—Arrangements at the receiver end

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L25/00—Baseband systems
 H04L25/02—Details ; Arrangements for supplying electrical power along data transmission lines
 H04L25/03—Shaping networks in transmitter or receiver, e.g. adaptive shaping networks ; Receiver end arrangements for processing baseband signals
 H04L25/03006—Arrangements for removing intersymbol interference
 H04L25/03178—Arrangements involving sequence estimation techniques
 H04L25/03203—Trellis search techniques

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L27/00—Modulatedcarrier systems
 H04L27/26—Systems using multifrequency codes
 H04L27/2601—Multicarrier modulation systems
 H04L27/2626—Arrangements specific to the transmitter
 H04L27/2627—Modulators

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L27/00—Modulatedcarrier systems
 H04L27/26—Systems using multifrequency codes
 H04L27/2601—Multicarrier modulation systems
 H04L27/2647—Arrangements specific to the receiver
 H04L27/2649—Demodulators

 H—ELECTRICITY
 H04—ELECTRIC COMMUNICATION TECHNIQUE
 H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
 H04L5/00—Arrangements affording multiple use of the transmission path
 H04L5/02—Channels characterised by the type of signal
 H04L5/04—Channels characterised by the type of signal the signals being represented by different amplitudes or polarities, e.g. quadriplex
Abstract
Description
This patent filing is a continuation in part of application Ser. No. 12/380,668 filed on Mar. 3, 2009.
I. Field of the Invention
The present invention relates to cellular communications and also relates to the Nyquist rate for data symbol transmission, the Shannon bound on communications capacity, and symbol modulation and demodulation for highdatarate satellite, airborne, wired, wireless, and optical communications and includes all of the communications symbol modulations and the future modulations for single links and multiple access links which include electrical and optical wired, mobile, pointtopoint, pointtomultipoint, multipointtomultipoint, cellular, multipleinput multipleoutput MIMO, and satellite communication networks. In particular it relates to WiFi, WiMax and longterm evolution LTE for cellular communications and satellite communications. WiFi, WiMax use orthogonal frequency division multiplexing OFDM on both links and LTE uses SCOFDM on the uplink from user to base station and OFDM on the downlink form base station to user. WiMax occupies a larger frequency band than WiFi and both use OFDM waveforms. SCOFDM is a single carrier orthogonal waveform version of OFDM which uses orthogonal frequency subbands of varying widths.
II. Description of the Related Art
Two fundamental bounds on communications are the Nyquist rate and the Shannon capacity theorem. The Nyquist rate is the complex digital sampling rate equal to B that is sufficient to include all of the information within a frequency band B. For communications, equivalent expressions for the Nyquist rate bound are defined in equations (1).
T _{s}≧1/B (1)
BT_{S}≧1
wherein 1/T_{s }is the data symbol transmission rate in the frequency band B which means T_{s }is the spacing between the data symbols.
The Shannon bound for the maximum data rate C is a bound on the corresponding number of information bits per symbol b as well as a bound on the communications efficiency η and is complemented by the Shannon coding theorem, and are defined in equations (2).
3 Shannon coding theorem for the information bit rate R_{b }

 For R_{b}<C there exists codes which support reliable communications
 For R_{b}>C there are no codes which support reliable communications
wherein E_{b}/N_{o }is the ratio of energy per information bit E_{b }to the noise power density N_{o}, max{b} is the maximum value of the number of information bits per symbol b and also is the information rate in Bps/Hz, and since the communications efficiency η=b/(T_{S}B) in bits/sec/Hz it follows that maximum values of b and η are equal. Derivation of the equation for E_{b}/N_{o }uses the definition E_{b}/N_{o}=(S/N)/b in addition to 1 and 2. Reliable communications in the statement of the Shannon coding theorem 3 means an arbitrarily low bit error rate BER.
OFDM is defined in
This invention introduces a maximum likelihood ML demodulation architecture and implementation of a quadrature layered modulation QLM for OFDM and SCOFDM modulations to provide a method for increasing the data rates. QLM for OFDM WiFi provides a method for increasing the data rates to 4.75× WiFi maximum data rate with current technology (4.75 times the WiFi maximum rate) and to 6× WiFi maximum data rate with technology advances. QLM provides similar increases in data rate for OFDM WiMax and SCOFDM LTE. QLM supports data symbol rates that can be multiples of the Nyquist rate and communications data rates that can be multiples of the Shannon bound.
A representative OFDM QLM architecture using ML demodulation is disclosed in this invention for WiFi standard and the transmit and receive signal processing algorithms and supporting block diagrams are developed to illustrate the architecture and implementation. This architecture is directly applicable to WiMax by increasing the number of OFDM tones to occupy the increased WiMax frequency band and also is directly applicable to SCOFDM since the OFDM QLM ML architecture uses a pulseshaped OFDM which partitions the frequency band into orthogonal subbands that can be combined to enable users to use differing frequency bands to implement SCOFDM.
QLM is a layered topology for transmitting higher data rates than possible with a single layer of communications and is implemented by transmitting each layer with a differentiating parameter which enables separation and decoding of each layer. For a representative OFDM architecture the OFDM WiFi QLM transmits the QLM signals over a set of subbands which together occupy the same frequency band as the WiFi standard 48 data symbol modulated FFT^{−1 }tones and over the WiFi 4 μs data packet. Computationally efficient fast multichannel FFT^{−1 }and FFT algorithms generate the subband QLM data symbols for transmission and implement the receive detection followed by maximum likelihood ML demodulation, which can be implemented with a chip architecture that supports both OFDM WiFi and the OFDM WiFi QLM in this invention disclosure as well as both OFDM WiMax and OFDM WiMax QLM with an increase in the frequency band, and with parameter changes the chip architecture supports both SCOFDM LTE and SCOFDM LTE QLM uplinks and both OFDMA LTE and OFDMA LTE QLM downlinks. Monte Carlo Matlab direct error count biterrorrate BER simulations for ML demodulation used in OFDM WiFi QLM demonstrate the QLM performance.
A multiscale MS code can be implemented with modest complexity in order to improve the biterrorrate BER performance of OFDM WiFi QLM by spreading each transmitted data symbol over the OFDM WiFi QLM data band and over the 4 μs data packet. Jensen's inequality from mathematical statistics proves that this uniform spreading of the Tx signals using MS provides the best communications BER performance.
The abovementioned and other features, objects, design algorithms, and performance advantages of the present invention will become more apparent from the detailed description set forth below when taken in conjunction with the drawings and performance data wherein like reference characters and numerals denote like elements and in which:
OFDM and SCOFDM applications of quadrature layered modulation QLM in this invention disclosure are illustrated by the WiFi 802.16 standard which uses OFDM on both uplinks and downlinks between the user and base station for cellular communications as well as for communications with satellites. OFDM WiFi QLM replaces the OFDM orthogonal data symbol tones with orthogonal subbands which are the same architecture as SCOFDM used for the LTE uplink. This means the OFDM WiFi QLM architecture is directly applicable to WiMax by simply increasing the number of subbands since they both use the same OFDM and 4 μs data packets with WiMax using a larger frequency band, and also is directly applicable to the LTE uplink since the OFDM WiFi QLM orthogonal subbands partition the frequency spectrum using the same architecture as SCOFDM for LTE to allow the various users to be assigned differing orthogonal frequency subbands across the frequency band and the QLM data symbol waveforms in these subbands are SCOFDM subband shaped waveforms used for LTE. The OFDM WiFi QLM architecture is directly applicable to LTE downlinks which use OFDM.
OFDM WiFi QLM uses maximum likelihood ML demodulation of the quadrature layered modulation QLM received correlated data symbols to support an architecture and implementation for QLM communications using the WiFi 4 μs data packet over the 20 MHz WiFi band for the WiFi standard and with obvious extensions to the other WiFi versions.
wherein [“o”] is the value of “o” for the communications channel when there is no layering.
The equations for the nonoptimized channel capacity in Bps and information bits b per symbol interval are the Shannon's bounds in 1,2 in equation (2) with the maximum “max” removed, with the [S/N] scaling in equations (3), and with the multiplication by “n_{p}” to account for the n_{p }layers. We find
using the definition b=CB in Bps/Hz=Bits/symbol from 2 in equations (2) and observing that “Bits/symbol” in 2 is “Bits/symbol interval” for QLM and wherein it is understood that the C,b are nonoptimized values with respect to the selection of the n_{p}.
New upper bounds on C, b, η and a new lower bound on E_{b}/N_{o }are derived in equations (5) by using equation (4) and equation (2). We find
wherein the maximum values of C, max{b}, and max{η} of C, b, η are the respective maximums of the expressions in equation (4) with respect to n_{p}, the units of C, b, η are Bps, information bits/symbol interval, and Bps/Hz which means b is expressed in units Bps/Hz as well as in units of information bits/symbol interval, and the min{E_{b}/N_{o}} is the minimum of E_{b}/N_{o }with respect to n_{p }similar to the derivation in 2 in equations (2).
The new coding theorem in 4 in equations (5) states that C is the upper bound on the information data rate R_{b }in bits/second for which error correcting codes exist to provide reliable communications with an arbitrarily low bit error rate BER wherein C is defined in 1 in equations (5) and upgrades the Shannon coding theorem 3 in equations (1) using new capacity bound C in 1 in equations (5) and introduces the new data symbol rate 5 whose maximum value max{n_{p}/T_{s}} is n_{p }times the Nyquist rate for a single channel.
QLM demodulation received signal processing synchronizes and removes the received waveform by performing a convolution of the received waveform encoded data symbol with the complex conjugate of this waveform, to detect the correlated data symbols. This convolution is a correlation of the waveform with itself as illustrated in
In
y(k)=H×(k)+u(k) (6)
wherein

 Y(k)=N_{s}×1 detected symbol vector. in subband k.
 H=N_{s}×N_{s }correlation matrix of data symbols
 x(k)=N_{s}×1 data symbol vector for layered channels in subband k
 u(k)=N_{s}×1 demodulation plus link noise vector for subband k
wherein the Rx data symbol vector y(k) elements are y(sk) which is the Rx detected correlated signal for state s=symbol s for subband k, the data symbol vector x(k) elements are x(sk) which is the Tx data symbol x(sk) for symbol s, u(k) is the noise vector, and “x” is the multiply operator. In this disclosure the same notation will be used for the estimates x(k), x(sk) and for the true values x(k),x(sk) respectively with the interpretation defined in the text. Equation (7) lists the ML solution. We find
since the inverse H^{−1 }exists for all applications of interest, and wherein H′ is the conjugate transpose of H, and 2σ^{2 }is the meansquare data symbol detection noise.
FIGS. 8,9 measure the Monte Carlo bit error rate BER vs. the scaled (E_{b}/N_{o})/n_{p }from equations (3) for the 3data symbol and 4data symbol groups in the OFDM WiFi QLM architecture in
The OFDM WiFi QLM performance calculations in
2 Scaling laws from equations (3) are
E _{b} /N _{o} =[E _{b} /N _{o}]+10 log_{10}(n _{p})
S/N=[S/N]+20 log_{10}(n _{p})

 wherein [“o”] is the value of “o” for the communications channel when there is no layering
OFDM WiFi QLM examples in equations (9) illustrate the performance calculated in
The OFDM WiFi QLM maximum information rate b in equations (9) is listed in 1 in equations (10) and the corresponding Tx maximum data rate R_{b }vs the WiFi 256QAM maximum data rate is calculated in 2 in equations (10). We find
wherein the Tx maximum QLM256QAM data rate R_{b }in Bps is scaled from the b for the WiFi maximum data rate calculated in 3 in
Consider the generation of a data symbol x(sk) waveform encoded baseband signal z(i_{0}s, Δ) for state s=signal s for processing block Δ and for all of the subbands k. We find

 z(i_{0}s, Δ)=[1×N]_{s }baseband signal vector indexed on i_{0 }in block Δ of (12) the waveform Ψencoded data symbols x(sk) for all k wherein w is a real symmetric Wavelet or equivalent waveform impulse response suitable for postweighted FFT^{−1 }subband datafilter waveforms
which is a computationally efficient postweighted FFT^{−1}{x(sk)} that calculates a [1×N]_{x }row vector indexed on i_{0 }and with each element i_{0 }multiplied by the corresponding element Ψ(i_{0}+i_{r}+(s−1)N/n_{p}+Δ(s)N) of the [1×N]_{Ψ} postweighting Ψ row vector. It is convenient to use vector and matrix notation in order to map these algorithms into hardware chips. Definitions used are defined in equations (13).

 [1=N]_{Ψ}=postweighting Ψ row vector indexed on i_{0 }with elements
Ψ(i_{0}+i_{r}+(s−1)N/n_{p}+Δ(s)N)
 [1=N]_{Ψ}=postweighting Ψ row vector indexed on i_{0 }with elements
Step 2 in 12 calculates the Matlab elementbyelement product “*” of the [1×N]_{x }row vector in step 1 with the [1×N}_{Ψ} row vector whose elements are the Ψ values Ψ(i_{0}+i_{r}+(s−1)N/n_{p}+Δ(s)N) defined in equations (13), to implement the computationally efficient postweighted FFT^{−1 }algorithm in equations (12) to calculate the [1×5N]_{s }row vector z(i_{0}s, Δ).
Step 3 in 13 unfolds the baseband waveform z(i_{0}s, Δ) over all of the data processing blocks Δ and adds zeros at both ends to expand the baseband waveform to fill the OFDM WiFi QLM 4 μs data packet with the resultant [1×5N]_{s }baseband vector z(is) which is the Tx signal for state s symbol s indexed by I over the 4 μs data packet. Vector unfolding as described in 13 consists of applying the Matlab operation of forming the [1×5N]_{s }vector by first laying out the [1×N]_{s }vectors z(i_{0}s, Δ) for all data processing blocks Δ and than adding zero row vectors z(start) and z(finish) if necessary to complete the [1×5N] 4 μs data packet vector z(is) for state s symbol s.
Step 4 in 14 is the final step in the implementation and generates the Tx [1×5N]_{z }baseband signal vector z(i) for all of the states s and signals s over the 4 μs OFDM WiFi QLM data packet by vector addition of the [1×5N]_{s }vectors z(is) over all values of state s symbol s.
The computationally complexity of the preweighted FFT^{−1 }algorithm including the addition of the vectors over the states and signals to generate z(i) in Step 4 is the following wherein M=log_{2}(N). We find
The Npoint postweighted FFT^{−1 }for Tx and preweighted FFT for Rx have nominal values equal to N=16 which yields a 20 MHz digital sample (clock rate) equal to the WiFi 20 MHz band and N=16 digital samples over the data symbol interval and which supports a layering menu n_{p}=1,2,4,8 since these integers are divisors of N=16. To increase the menu to n_{r}=1,2,3,4,6,8 requires N=24 which yields a 30 MHz clock rate and N=24 digital samples over the data symbol interval and allows the integers in the increased menu to be divisors of N=24. Higher values of N are required to add n_{p}=5,7 values to the menu.
Rx demodulation of the received Tx signal z(i) row vector [1×5N] plus noise starts by using preweighted FFT subband detection filters to recover the correlated data symbol estimates in the Tx signal plus noise at the clock intervals N/n_{p }for the 3,4data symbol groups layered with QLM communications channels in
The correlated signals recovered by the preweighted FFT subband detection filters are characterized by the correlation coefficients {h(s, s′)} wherein s is the reference data symbol for state s which in our application are the data signals correlated with the transmitted data signals s′ at the clock intervals N/n_{p}. There are N_{s}=(n_{s}−1)n_{p}+1 QLM data symbols transmitted over each subband of the WiFi 4 μs packet and for both Tx and Rx signal processing it is convenient to number them in the order they are received using the signal index s for state index s in equations (11).
The correlation coefficients h(s,s′) are evaluated starting with the definition of the data symbols x(sk), x(s′k) waveforms using the definitions in equations (11),(13). We find
The correlation coefficient h(s,s′) between data symbol x(sk) and data symbol x(s′k) in the same subband k is by definition equal to
wherein the correlation coefficients h(s,s′) are the row s and column s′ elements of the [N_{s}xN_{s}]_{h }correlation matrix H=[h(s,s′)].
The computationally efficient preweighted FFT subband filters detect y(sk) for state s in all of the subbands k by convolving the complex conjugate of the waveform of data symbol x(sk) at state s in the receiver with the Rx waveform z(i) in
wherein
wherein the presum is a [1×N]_{p }vector indexed on i_{0 }and the FFT of the presum in equations (17) is a computationally efficient preweighted (presummed) FFT set of detection filters which calculate the [1×12]_{y }vector whose elements are y(sk) for k=1, 2, . . . , 12 subbands by the matrix operation [1×N]_{p}[N×12]=[1×12]_{y }wherein [N×12] is the DFT matrix equivalent of the FFT.
Step 2 in 22 calculates the FFT of this presum vector to implement the computationally efficient preweighted FFT which generates the [1×12]_{y }correlated signal vector y(s)=[y(sk=1) y(sk=2) . . . y(sk=12)] by the equivalent DFT [N×12] matrix multiplication [1×N]_{p}[N×12]=[1×12]_{5}, on the [1×1N]_{p }presum vector in step 1.
Step 3 in 23 repeats steps 1 & 2 for all of the states s=1, 2, . . . , N_{s}=(n_{s}−1) n_{p}+1 to generate the [N_{s}×12] correlated signal matrix Y with [1×12]_{y }row vectors y(s) for each row s and [N_{x}×1] column vectors y(k)=[y(s=1k); y(s=2k); . . . ; y(N_{s}k)} for each column k using Matlab operations to generate this column vector
Step 4 in 24 calculates the computationally efficient solution of the ML equation for each column y(k) of Y by solving x(k)=y(k) in 4 in equations (7) for the [N_{s}×1] column vector x(k)=[x(s=1k); x(s=2k); . . . ; x(s=N_{s}k)] using Matlab operations to construct the column vector whose elements x(sk) are the Rx estimates for data symbol s for subband k.
Step 5 in 25 recovers the data words for each estimate x(sk) and softdecision decodes the data word bits to recover the information bits in each data word.
The computational complexity of the preweighted FFT algorithm for the 4 μs packet is the Following wherein M=log_{2}(N). We find
It is well known that the ML solution has a fast algorithm whose computational complexity is estimated to be
wherein M_{s}=log_{2 }(N_{s}) and taking into account the number of subbands equal to 12. For a fast algorithm to apply it is necessary to remove one symbol from the n=1 ground layer in order to make the number of symbols in a 4 μS packet equal to a product of primes rather than a single prime.
Jensen's inequality from “Mathematical Statistics” by Fergeson, Academic Press, 1967 is a fundamental lemma and when applied to OFDM WiFi QLM proves that a uniform spreading of the Tx signals using multiscale MS encoding of each QLM layer of communicatons provides the best communications BER performance. This means that there are no other coding or spreading schemes for WiFi which can improve the BER performance provided by MS OFDM WiFi QLM. MS encoding spreads each data symbol over each 4 μs packet in each subband and simultaneously over all of the subbands. This MS OFDM WiFi QLM mode is disclosed using a representative implementation with complex Walsh CDMA codes and generalized complex Walsh CDMA codes and equally applies to all orthogonal and semiorthogonal spreading codes.
In the MS OFDM WiFi QLM mode the transmit data symbols x(sn, ∀ k) in each layer n are generated by encoding the transmit data symbols x(un) with the [N_{c}×N_{c}] MS code matrix C=[C(u_{0}+u_{1}N_{0}, n_{p}+n_{1}N_{0})] prior to the transmit signal processing in
Received estimates of the transmit data symbols x(s=n_{0}+1n, k=n_{1}+1) in each layer n are MS decoded in equation (21) to generate the estimates x(un) of the data symbols for u in layer n and prior to MS encoding in the transmitter. We find
using the orthgonality property of C
N _{c} ^{−1}Σ_{n0,n1} C(u _{0} +u _{1} N _{0} ,n _{0} +n _{1} N _{0})C*(u _{0} +u _{1} N _{0} ,n _{0} +n _{1} N _{0})=δ(u,u)

 wherein
Transmitted data symbols x(un) for the MS OFDM WiFi QLM mode are the transmitted data symbols x(sk) for the OFDM WiFi QLM mode with the equivalence that user indices u_{0}=0, 1, . . . , N_{0}−1 and s=1, 2, . . . , N_{0 }refer to the same data symbols, and k=1, 2 . . . , N_{1 }refer to the same data symbols, and the MS encoding mode is implemented before the transmit signal processing in
wherein M_{c}=log_{2}(N_{c}) and N_{c}=n_{s}−1 for n>1 and for n=1 assuming N_{c}=n_{s}−1 which corresponds to neglecting the last symbol order to have a fast algorithm for all n.
Signal processing 50 in
This OFDM WIFi QLM architecture applies with parameter changes to the other WiFi options, to WiMax which has a larger frequency band, to the LTE downlink which also uses OFDM, and to the LTE uplink since the QLM architecture generates shaped contiguous subbands which are SCOFDM.
LTE uplink uses SCOFDM filter banks which are weighted FFT^{−1 }tone filters with the LTE transmission partitioned into subframe and frame lengths. LTE filters can be combined into user subbands over the frequency band with each user subband consisting of the weighted tone filters over the user subband frequency band. OFDM QLM ML generates the same weighted FFT^{−1 }tone filters by combining each set of 4 FFT^{1 }tones for the 64 point FFT^{−1 }for WiFi standard into a weighted subband filter which subband filter is a weighted FFT^{−1 }tone filter for a 64/4=16 point FFT^{−1}. This means the OFDM QLM ML architecture developed in this specification directly applies to the LTE uplink with parameter changes for the weighted FFT^{−1 }filter spacing, number of filters and frequency band, subframe and frame lengths, and communication protocols. In particular this means the QLM ML 2,3,4data group architecture for transmission of n_{p }layers or channels of QLM communications can be implemented for the LTE uplink communications and with comparable performance as the OFDM QLM ML communications assuming the frame efficiency for OFDM QLM ML is the same as implemented on the LTE uplink. LTE downlink uses OFDM and which means the OFDM QLM ML architecture in this specification is directly applicable to the LTE downlink.
The ML modulation and demodulation architectures and algorithms and implementations and filings disclosed in this patent for OFDM QLM are examples of available ML, MAP, trellis data symbol, trellis data bit, recursive relaxation, and other optimization architectures and algorithms to recover estimates of data symbols from layered communications channels for the plurality of applications with differentiating parameters that enable demodulation algorithms to recover estimates of the data symbols and for the trellis algorithms to recover the data in the modulated data symbols, in each of the communications layers or channels. This patent covers the plurality of all of these architectures, algorithms, implementations, and filings for generation and for recovery of the data symbols in each of the communications layers as well as decoding of the data symbols.
This patent covers the plurality of everything related to QLM generation for WiFi, WiMax, LTE and OFDM/OFDMA, SCOFDM waveforms, QLM demodulation for WiFi, WiMax, LTE and OFDM/OFDM, SCOFDM waveforms, and data recovery of QLM and to the corresponding bounds on QLM to all QLM inclusive of theory, teaching, examples, practice, and of implementations for related technologies. The representative trellis and ML algorithms for QLM demodulation are examples to illustrate the methodology and validate the performance and are representative of all QLM demodulation algorithms including all maximum likelihood ML architectures, maximum a posteriori MAP, maximum a priori, finite field techniques, direct and iterative estimation techniques, trellis symbol and iterative trellis symbol and with/without simplifications, trellis bit and iterative trellis bit and with/without simplifications and with/without bit error correction coding, and all other related algorithms whose principal function is to recover estimates of the transmitted symbols for QLM parallel layered modulation as well as data recovery related to QLM and the QLM bounds.
Preferred embodiments in the previous description of modulation and demodulation algorithms and implementations for QLM for the known modulations: and demodulations and for all future modulations and demodulations, are provided to enable any person skilled in the art to make or use the present invention. The various modifications to these embodiments will be readily apparent to those skilled in the art and the generic principles defined herein may be applied to other embodiments without the use of the inventive faculty. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the wider scope consistent with the principles and novel features disclosed herein. Additional filings for QLM signal processing and bound include the plurality of information theoretic filings with examples being radar, imaging, and media processing.
Claims (6)
C=max{n _{p} B log_{2}(1+(S/N)/n _{p}^2)}
max{b}=max{n _{p}(1+(S/N)/n _{p}^2)},
max(η)=max{b},
min{E _{b} /N _{o}}=min{[n _{p}^2/b][2^b}/n _{p}−1]}
Priority Applications (2)
Application Number  Priority Date  Filing Date  Title 

US12/380,668 US7855995B1 (en)  20080211  20090303  QLM maximum likelihood demodulation 
US12/587,687 US7907512B1 (en)  20090303  20091013  OFDM and SCOFDM QLM 
Applications Claiming Priority (1)
Application Number  Priority Date  Filing Date  Title 

US12/587,687 US7907512B1 (en)  20090303  20091013  OFDM and SCOFDM QLM 
Related Parent Applications (1)
Application Number  Title  Priority Date  Filing Date  

US12/380,668 ContinuationInPart US7855995B1 (en)  20021008  20090303  QLM maximum likelihood demodulation 
Publications (1)
Publication Number  Publication Date 

US7907512B1 true US7907512B1 (en)  20110315 
Family
ID=43708171
Family Applications (1)
Application Number  Title  Priority Date  Filing Date 

US12/587,687 Active US7907512B1 (en)  20080211  20091013  OFDM and SCOFDM QLM 
Country Status (1)
Country  Link 

US (1)  US7907512B1 (en) 
Cited By (17)
Publication number  Priority date  Publication date  Assignee  Title 

US20100269007A1 (en) *  20090416  20101021  Lockheed Martin Corporation  Digitized radar information redundancy method and system 
US20130157600A1 (en) *  20111220  20130620  Postech AcademyIndustry Foundation  Method and apparatus for detecting radio signal 
US8630362B1 (en)  20110502  20140114  Urbain A. von der Embse  QLM costate MAP trellis 
US8917786B1 (en) *  20130509  20141223  Urbain Alfred von der Embse  QLM communications faster than Shannon rate 
US9197364B1 (en)  20150212  20151124  Urbain A. von der Embse  Scaling for QLM communications faster than shannon rate 
US9231813B1 (en)  20150507  20160105  Urbain A. von der Embse  Communications faster than Shannon rate 
CN106352244A (en) *  20160831  20170125  中国石油化工股份有限公司  Pipeline leakage detection method based on hierarchical neural network 
US20170041054A1 (en) *  20140422  20170209  Huawei Technologies Co., Ltd.  Signal Transmission Apparatus and Downlink Signal Transmission Method 
US20170134118A1 (en) *  20140729  20170511  Cable Television Laboratories, Inc.  Systems and methods for providing resilience to lte signaling interference in wifi 
US20170149520A1 (en) *  20100506  20170525  Sun Patent Trust  Communication method and communication apparatus 
US9960945B2 (en) *  20160217  20180501  Innowireless Co., Ltd.  Method of processing WCDMA signal timing offset for signal analyzing equipment 
US10158555B2 (en)  20160929  20181218  At&T Intellectual Property I, L.P.  Facilitation of route optimization for a 5G network or other next generation network 
US10171214B2 (en)  20160929  20190101  At&T Intellectual Property I, L.P.  Channel state information framework design for 5G multiple input multiple output transmissions 
US10206232B2 (en)  20160929  20190212  At&T Intellectual Property I, L.P.  Initial access and radio resource management for integrated access and backhaul (IAB) wireless networks 
US10355813B2 (en)  20170214  20190716  At&T Intellectual Property I, L.P.  Link adaptation on downlink control channel in a wireless communications system 
US10602507B2 (en) *  20160929  20200324  At&T Intellectual Property I, L.P.  Facilitating uplink communication waveform selection 
US10644924B2 (en)  20160929  20200505  At&T Intellectual Property I, L.P.  Facilitating a twostage downlink control channel in a wireless communication system 
Citations (28)
Publication number  Priority date  Publication date  Assignee  Title 

US6426723B1 (en)  20010119  20020730  Nortel Networks Limited  Antenna arrangement for multiple input multiple output communications systems 
US20020136190A1 (en) *  20010326  20020926  Yoshiyuki Hata  Banddivision demodulation method and OFDM receiver 
US6504506B1 (en)  20000630  20030107  Motorola, Inc.  Method and device for fixed in time adaptive antenna combining weights 
US20030063680A1 (en) *  20010928  20030403  Nec Usa, Inc.  Perbin DFE for advanced OQAMbased multicarrier wireless data transmission systems 
US6636568B2 (en)  20020301  20031021  Qualcomm  Data transmission with nonuniform distribution of data rates for a multipleinput multipleoutput (MIMO) system 
US6647078B1 (en)  20000630  20031111  Motorola, Inc.  Method and device for multiuser frequencydomain channel estimation based on gradient optimization techniques 
US6674712B1 (en)  19980908  20040106  Samsung Electronics Co., Ltd.  Device and method for generating quaternary complex quasiorthogonal code and spreading transmission signal using quasiorthogonal code in CDMA communication system 
US6728517B2 (en)  20020422  20040427  Cognio, Inc.  Multipleinput multipleoutput radio transceiver 
US6731668B2 (en)  20010105  20040504  Qualcomm Incorporated  Method and system for increased bandwidth efficiency in multiple input—multiple output channels 
US6731618B1 (en)  20001020  20040504  Airvana, Inc.  Coding for multiuser communication 
US20040141570A1 (en) *  20020220  20040722  Kenichiro Yamazaki  Symbol timing correction circuit, receiver, symbol timing correction, mothed, and demodulation processing method 
US6798737B1 (en)  19991006  20040928  Texas Instruments Incorporated  Use of WalshHadamard transform for forward link multiuser detection in CDMA systems 
US6856652B2 (en)  19981111  20050215  Cyntrust Communications, Inc.  Bandwidth efficient QAM on a TDMFDM system for wireless communications 
US7010048B1 (en)  19980212  20060307  Aqvity, Llc  Multiple access method and system 
US20060239226A1 (en) *  20050421  20061026  Samsung Electronics Co., Ltd.  System and method for channel estimation in a delay diversity wireless communication system 
US7277382B1 (en)  20010109  20071002  Urbain A. von der Embse  Hybrid walsh encoder and decoder for CDMA 
US20070297529A1 (en) *  20051117  20071227  Shengli Zhou  Recursive and trellisbased feedback reduction for MIMOOFDM with ratelimited feedback 
US7337383B1 (en)  20040206  20080226  Urbain A. von der Embse  Decisioning rules for turbo and convolutional decoding 
US7352796B1 (en)  20010213  20080401  Urbain Alfred von der Embse  Multiple data rate complex Walsh codes for CDMA 
US7376688B1 (en)  20010109  20080520  Urbain A. von der Embse  Wavelet multiresolution waveforms 
US20080137718A1 (en) *  20061207  20080612  Interdigital Technology Corporation  Wireless communication method and apparatus for allocating training signals and information bits 
US7391819B1 (en)  20021008  20080624  Urbain Alfred von der Embse  Capacity bound and modulation for communications 
US7394792B1 (en)  20021008  20080701  Urbain A. von der Embse  Multiscale CDMA 
US20080159442A1 (en) *  20061227  20080703  Yasuhiko Tanabe  Wireless communication apparatus and receiving method 
US7558310B1 (en)  20010109  20090707  Urbain Alfred von der Embse  Multiscale code division frequency/wavelet multiple access 
US20090276671A1 (en) *  20080505  20091105  Industrial Technology Research Institute  Methods and apparatus for transmitting/receiving data in a communication system 
US20100098195A1 (en) *  20081020  20100422  Michael Nekhamkin  Systems and methods for frequency offset correction in a digital radio broadcast receiver 
US20100166088A1 (en) *  20081231  20100701  Bernard Arambepola  Method and system for ofdm symbol timing recovery 

2009
 20091013 US US12/587,687 patent/US7907512B1/en active Active
Patent Citations (28)
Publication number  Priority date  Publication date  Assignee  Title 

US7010048B1 (en)  19980212  20060307  Aqvity, Llc  Multiple access method and system 
US6674712B1 (en)  19980908  20040106  Samsung Electronics Co., Ltd.  Device and method for generating quaternary complex quasiorthogonal code and spreading transmission signal using quasiorthogonal code in CDMA communication system 
US6856652B2 (en)  19981111  20050215  Cyntrust Communications, Inc.  Bandwidth efficient QAM on a TDMFDM system for wireless communications 
US6798737B1 (en)  19991006  20040928  Texas Instruments Incorporated  Use of WalshHadamard transform for forward link multiuser detection in CDMA systems 
US6504506B1 (en)  20000630  20030107  Motorola, Inc.  Method and device for fixed in time adaptive antenna combining weights 
US6647078B1 (en)  20000630  20031111  Motorola, Inc.  Method and device for multiuser frequencydomain channel estimation based on gradient optimization techniques 
US6731618B1 (en)  20001020  20040504  Airvana, Inc.  Coding for multiuser communication 
US6731668B2 (en)  20010105  20040504  Qualcomm Incorporated  Method and system for increased bandwidth efficiency in multiple input—multiple output channels 
US7558310B1 (en)  20010109  20090707  Urbain Alfred von der Embse  Multiscale code division frequency/wavelet multiple access 
US7277382B1 (en)  20010109  20071002  Urbain A. von der Embse  Hybrid walsh encoder and decoder for CDMA 
US7376688B1 (en)  20010109  20080520  Urbain A. von der Embse  Wavelet multiresolution waveforms 
US6426723B1 (en)  20010119  20020730  Nortel Networks Limited  Antenna arrangement for multiple input multiple output communications systems 
US7352796B1 (en)  20010213  20080401  Urbain Alfred von der Embse  Multiple data rate complex Walsh codes for CDMA 
US20020136190A1 (en) *  20010326  20020926  Yoshiyuki Hata  Banddivision demodulation method and OFDM receiver 
US20030063680A1 (en) *  20010928  20030403  Nec Usa, Inc.  Perbin DFE for advanced OQAMbased multicarrier wireless data transmission systems 
US20040141570A1 (en) *  20020220  20040722  Kenichiro Yamazaki  Symbol timing correction circuit, receiver, symbol timing correction, mothed, and demodulation processing method 
US6636568B2 (en)  20020301  20031021  Qualcomm  Data transmission with nonuniform distribution of data rates for a multipleinput multipleoutput (MIMO) system 
US6728517B2 (en)  20020422  20040427  Cognio, Inc.  Multipleinput multipleoutput radio transceiver 
US7391819B1 (en)  20021008  20080624  Urbain Alfred von der Embse  Capacity bound and modulation for communications 
US7394792B1 (en)  20021008  20080701  Urbain A. von der Embse  Multiscale CDMA 
US7337383B1 (en)  20040206  20080226  Urbain A. von der Embse  Decisioning rules for turbo and convolutional decoding 
US20060239226A1 (en) *  20050421  20061026  Samsung Electronics Co., Ltd.  System and method for channel estimation in a delay diversity wireless communication system 
US20070297529A1 (en) *  20051117  20071227  Shengli Zhou  Recursive and trellisbased feedback reduction for MIMOOFDM with ratelimited feedback 
US20080137718A1 (en) *  20061207  20080612  Interdigital Technology Corporation  Wireless communication method and apparatus for allocating training signals and information bits 
US20080159442A1 (en) *  20061227  20080703  Yasuhiko Tanabe  Wireless communication apparatus and receiving method 
US20090276671A1 (en) *  20080505  20091105  Industrial Technology Research Institute  Methods and apparatus for transmitting/receiving data in a communication system 
US20100098195A1 (en) *  20081020  20100422  Michael Nekhamkin  Systems and methods for frequency offset correction in a digital radio broadcast receiver 
US20100166088A1 (en) *  20081231  20100701  Bernard Arambepola  Method and system for ofdm symbol timing recovery 
NonPatent Citations (10)
Title 

C.E. Shannon "A Mathematical Theory of Communications", Bell System Technical Journal, 27:379423, 623656, Oct. 1948. 
Hanzo, C.H. Wong, M.S. Lee's book "Adaptive Wireless Transceivers", John Wiley & Sons 2002. 
J.G. Proakis's book "Digital Communications". McGraw Hill, Inc. 1995. 
Thomas S. Ferguson's book "Mathematical Statistics", Academic Press 1967. 
U.S. Appl. No. 11/131,464, filed May 18, 2005, von der Embse. 
U.S. Appl. No. 12/069,418, filed Feb. 11, 2008, von der Embse. 
U.S. Appl. No. 12/151,986, filed May 12, 2008, von der Embse. 
U.S. Appl. No. 12/152,318, filed May 13, 2008, von der Embse. 
U.S. Appl. No. 12/380,668, filed Mar. 3, 2009, von der Embse. 
Vucetec and J. Yuan's book "Turbo Codes", Kluwer Academic Publishers 2000. 
Cited By (27)
Publication number  Priority date  Publication date  Assignee  Title 

US8429484B2 (en) *  20090416  20130423  Lockheed Martin Corporation  Digitized radar information redundancy method and system 
US20100269007A1 (en) *  20090416  20101021  Lockheed Martin Corporation  Digitized radar information redundancy method and system 
US20170149520A1 (en) *  20100506  20170525  Sun Patent Trust  Communication method and communication apparatus 
US10305619B2 (en)  20100506  20190528  Sun Patent Trust  Communication method and communication apparatus 
US9948421B2 (en) *  20100506  20180417  Sun Patent Trust  Communication method and communication apparatus 
US8630362B1 (en)  20110502  20140114  Urbain A. von der Embse  QLM costate MAP trellis 
US9026054B2 (en) *  20111220  20150505  Lg Electronics Inc.  Method and apparatus for detecting radio signal 
US20130157600A1 (en) *  20111220  20130620  Postech AcademyIndustry Foundation  Method and apparatus for detecting radio signal 
US8917786B1 (en) *  20130509  20141223  Urbain Alfred von der Embse  QLM communications faster than Shannon rate 
US9998188B2 (en) *  20140422  20180612  Huawei Technologies Co., Ltd  Signal transmission apparatus and downlink signal transmission method 
US20170041054A1 (en) *  20140422  20170209  Huawei Technologies Co., Ltd.  Signal Transmission Apparatus and Downlink Signal Transmission Method 
US10122494B2 (en) *  20140729  20181106  Cable Television Laboratories, Inc.  Systems and methods for providing resilience to LTE signaling interference in WiFi 
US20170134118A1 (en) *  20140729  20170511  Cable Television Laboratories, Inc.  Systems and methods for providing resilience to lte signaling interference in wifi 
US10091769B2 (en)  20140729  20181002  Cable Television Laboratories, Inc.  LTE signaling in RF bands with competing communication systems 
US9197364B1 (en)  20150212  20151124  Urbain A. von der Embse  Scaling for QLM communications faster than shannon rate 
US9231813B1 (en)  20150507  20160105  Urbain A. von der Embse  Communications faster than Shannon rate 
US9960945B2 (en) *  20160217  20180501  Innowireless Co., Ltd.  Method of processing WCDMA signal timing offset for signal analyzing equipment 
CN106352244A (en) *  20160831  20170125  中国石油化工股份有限公司  Pipeline leakage detection method based on hierarchical neural network 
US10158555B2 (en)  20160929  20181218  At&T Intellectual Property I, L.P.  Facilitation of route optimization for a 5G network or other next generation network 
US10171214B2 (en)  20160929  20190101  At&T Intellectual Property I, L.P.  Channel state information framework design for 5G multiple input multiple output transmissions 
US10206232B2 (en)  20160929  20190212  At&T Intellectual Property I, L.P.  Initial access and radio resource management for integrated access and backhaul (IAB) wireless networks 
US10602507B2 (en) *  20160929  20200324  At&T Intellectual Property I, L.P.  Facilitating uplink communication waveform selection 
US10616092B2 (en)  20160929  20200407  At&T Intellectual Property I, L.P.  Facilitation of route optimization for a 5G network or other next generation network 
US10623158B2 (en)  20160929  20200414  At&T Intellectual Property I, L.P.  Channel state information framework design for 5G multiple input multiple output transmissions 
US10644924B2 (en)  20160929  20200505  At&T Intellectual Property I, L.P.  Facilitating a twostage downlink control channel in a wireless communication system 
US10687375B2 (en)  20160929  20200616  At&T Intellectual Property I, L.P.  Initial access and radio resource management for integrated access and backhaul (IAB) wireless networks 
US10355813B2 (en)  20170214  20190716  At&T Intellectual Property I, L.P.  Link adaptation on downlink control channel in a wireless communications system 
Similar Documents
Publication  Publication Date  Title 

US10567125B2 (en)  Modulation and equalization in an orthonormal timefrequency shifting communications system  
AU2014354845B2 (en)  System and method for radio frequency carrier aggregation  
KR20180030546A (en)  Simplex orthogonal timefrequency spatial modulation system  
KR20180030782A (en)  Orthogonal timefrequency spatial modulation system  
US20160315685A1 (en)  Transmission method,transmission device, receiving method, and receiving device  
US20170244524A1 (en)  Variable latency data communication using orthogonal time frequency space modulation  
US9042213B2 (en)  Communication apparatus and a communication method for combining signals mapped on a plurality of frequency bands and transforming the combined signal into a symbol in a time domain  
CN108141294B (en)  OFDMcompatible orthogonal timefrequencyspace communication system  
US10404514B2 (en)  Orthogonal time frequency space communication system compatible with OFDM  
US10411843B2 (en)  Orthogonal time frequency space communication system compatible with OFDM  
US10090973B2 (en)  Multiple access in an orthogonal time frequency space communication system  
US9893922B2 (en)  System and method for implementing orthogonal time frequency space communications using OFDM  
JP2014161071A (en)  Method and apparatus for pilot multiplexing in wireless communication system  
JP2014147082A (en)  Systems and methods for scfdma transmission diversity  
US20170099607A1 (en)  Multiple access in an orthogonal time frequency space communication system  
US9929783B2 (en)  Orthogonal time frequency space modulation system  
US20170149594A1 (en)  Symplectic orthogonal time frequency space modulation system  
CN100583708C (en)  Method and apparatus for performing digital communications  
US8385387B2 (en)  Time dependent equalization of frequency domain spread orthogonal frequency division multiplexing using decision feedback equalization  
US8270547B2 (en)  Channel estimation method and system for intercarrier interferencelimited wireless communication network  
ES2282300T3 (en)  Method and distributions in a telecommunications system.  
US7058140B2 (en)  Slidingwindow multicarrier frequency division multiplexing system  
CN100556012C (en)  The frequency domain equalization of singlecarrier signal  
US7643453B2 (en)  Legacy compatible spatial multiplexing systems and methods  
US7701839B2 (en)  Method and system for multirate multiuser modulation 
Legal Events
Date  Code  Title  Description 

STCF  Information on status: patent grant 
Free format text: PATENTED CASE 

REMI  Maintenance fee reminder mailed  
SULP  Surcharge for late payment  
FPAY  Fee payment 
Year of fee payment: 4 

FEPP  Fee payment procedure 
Free format text: MAINTENANCE FEE REMINDER MAILED (ORIGINAL EVENT CODE: REM.); ENTITY STATUS OF PATENT OWNER: SMALL ENTITY 

MAFP  Maintenance fee payment 
Free format text: PAYMENT OF MAINTENANCE FEE, 8TH YR, SMALL ENTITY (ORIGINAL EVENT CODE: M2552); ENTITY STATUS OF PATENT OWNER: SMALL ENTITY Year of fee payment: 8 

FEPP  Fee payment procedure 
Free format text: 7.5 YR SURCHARGE  LATE PMT W/IN 6 MO, SMALL ENTITY (ORIGINAL EVENT CODE: M2555); ENTITY STATUS OF PATENT OWNER: SMALL ENTITY 